SWAN-Idiap dataset is a multimodal biometric dataset (face, voice, and periocular) acquired using a smartphone. The SWAN-Idiap dataset comprises 150 subjects that are captured in six different sessions reflecting real-life scenarios of smartphone assisted authentication. One of the unique features of this dataset is that it is collected in four different geographic locations representing a diverse population and ethnicity. Additionally, it also contains a multimodal Presentation Attack (PA) or spoofing dataset using low-cost Presentation Attack Instruments (PAI) such as print and electronic display attacks. The novel acquisition protocols and the diversity of the data subjects collected from different geographic locations will allow developing a novel algorithm for either unimodal or multimodal biometrics.

CSMAD-Mobile is a dataset for mobile face recognition and presentation attack detection (anti-spoofing). The dataset contains face and silicon masks images captured with different smartphones. This dataset consists of images captured from 8 different Bona Fide subjects using three different smartphones (iPhone X, Samsung S7 and Samsung S8). For each subject within the database, varying number of samples are collected using all the three phones. Similarly, the silicone masks of each of the subject is collected using three phones.